The Global Artificial Intelligence in Agriculture Market Report includes a comprehensive analysis of the present market. The report starts with the basic Artificial Intelligence in Agriculture Market overview and then goes into each and every detail.
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The scale of Artificial Intelligence In Agriculture is getting bigger. Increased consumption and increased demand for crops are key drivers of demand for robots in agriculture.
The increase in consumption motivates farmers to expand agricultural operations. As farmers move more toward automation, unmanned aerial vehicles and robots have become an integral part of agriculture and agriculture.
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Because artificial intelligence is the backbone of robotic engineering, it is estimated that the adoption of robots in agriculture will contribute to the growth of the agricultural market.
Artificial Intelligence in Agriculture Market projected to grow at CAGR of +22% from 2018 to 2023
Artificial Intelligence in Agriculture Market offers an important analytical guidance on the trends and developments in this industry. The report also provides a professional and in-depth analysis on the global market while formulating industry insights into its current state of affairs.
The report offers details on the pricing structure and channels of distribution of equipment suppliers in the global industry.
Top Key Vendors:
IBM (US), John Deere (US), Microsoft (US), Agribotix (US), The Climate Corporation (US), ec2ce (Spain), Sky Squirrel Technologies, aWhere (US), Precision Hawk (US), Granular (US), and Autonomous Tractor Corporation (US)
The study presents a qualitative and quantitative analysis of the Artificial Intelligence in Agriculture Market, its key segments, regulatory landscape, and competitive scenario, and recent developments. A detailed analysis of factors expected to drive and challenge the growth of the market as well as the trends that decide consumer inclination.
The report utilizes a variety of primary and secondary research methodologies for gathering quantitative as well as qualitative data on global as well as regional fronts. With the help of a number of industry-best analytical methods, the vast amount of market data thus gathered is filtered and narrowed down to the details that matter the most to companies operating in the market or aspiring to enter it.
Further, the study offers an analysis of the current performance of the key regional markets for ship plate, namely Europe, South America, North America, the Middle East and Africa, and Asia Pacific, on the basis of a number of imperative market parameters, such as, the manufacturing volume, production capacity, pricing strategy, the dynamics of demand, supply, and sales, return on investments (RoI), and the growth rate of this market in each of the regions
The AI of the Agricultural Market Report has been classified by offer, technology, application and region. In addition, artificial intelligence in the agricultural market is classified as hardware, software, AI-as-a-Service and services.
This software segment will be held at the largest market size in 2016. The market is mainly driven by the integration of mobile technology and agricultural technology, systems.
In the last section of the report, the companies responsible for increasing the sales in the Artificial Intelligence in Agriculture Market has been presented. These companies have been analyzed in terms of their manufacturing base, basic information, and competitors.
In addition, the application and product type introduced by each of these companies also form a key part of this section of the report. The recent enhancements that took place in the global market and their influence on the future growth of the market have also been presented through this study.
Table of Content:
Global Artificial Intelligence in Agriculture Market Research Report 2018-2023
Chapter 1 Artificial Intelligence in Agriculture Market Overview
Chapter 2 Global Economic Impact
Chapter 3 Competition by Manufacturer
Chapter 4 Production, Revenue (Value) by Region (2018-2023)
Chapter 5 Supply (Production), Consumption, Export, Import by Regions (2018-2023)
Chapter 6 Production, Revenue (Value), Price Trend by Type
Chapter 7 Analysis by Application
Chapter 8 Manufacturing Cost Analysis
Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers
Chapter 10 Marketing Strategy Analysis, Distributors/Traders
Chapter 11 Market Effect Factors Analysis
Chapter 12 Market Forecast (2018-2023)
Chapter 13 Appendix
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